Instructions to use BiliSakura/BitDance-Tokenizer-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/BitDance-Tokenizer-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/BitDance-Tokenizer-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Update all files for BitDance-Tokenizer-diffusers
Browse files- ae_d32c256/config.json +21 -0
ae_d32c256/config.json
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{
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"_class_name": "BitDanceAutoencoder",
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"_diffusers_version": "0.36.0",
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"ddconfig": {
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"ch": 128,
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"ch_mult": [
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],
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"double_z": false,
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"in_channels": 3,
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"num_res_blocks": 4,
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"out_ch": 3,
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"z_channels": 256
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},
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"gan_decoder": true
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}
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